Downregulation of STOX1 is a novel prognostic biomarker for glioma patients
Abstract: Storkhead box 1 (STOX1) is a winged helix transcription factor structurally and functionally related to the forkhead family of transcription factors. Recent studies have highlighted its role in the central nervous system and revealed hints in the development of glioma. However, the expression profiles of STOX1, its association with clinicopathological characteristics, and potential functions in glioma remain unknown. In this study, we analyzed three publicly available datasets including CGGA, TCGA, and Rembrandt and revealed a grade-dependent reduction in STOX1 expression in glioma (P < 0.001). Chi-square test demonstrated that low STOX1 expression was significantly associated with older age at initial diagnosis (P < 0.001), less IDH1 mutation (P < 0.001), and advanced WHO grade (P < 0.001). Moreover, multivariate Cox regression analysis showed that STOX1 expression may serve as a novel independent prognostic biomarker in glioma patients. Bioinformatic functional analysis (GSEA) predicted that STOX1 was related to many key cancer pathways including P53 signaling pathway (P < 0.01), DNA replication (P < 0.05), homologous recombination (P < 0.05), and Wnt signaling pathway (P < 0.05). Taken together, these findings suggested that STOX1 may be used as a novel predictive molecular biomarker for glioma grading and overall patient survival. Further investigations on the functional roles and therapeutic value of STOX1 in glioma are warranted.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Downregulation of STOX1 is a novel prognostic biomarker for glioma patients ; volume:16 ; number:1 ; year:2021 ; pages:1164-1174 ; extent:11
Open life sciences ; 16, Heft 1 (2021), 1164-1174 (gesamt 11)
- Urheber
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Jin, Fei-qin
Jin, Lei
Wang, Yan-ling
- DOI
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10.1515/biol-2021-0119
- URN
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urn:nbn:de:101:1-2022091914065647122775
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:29 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Jin, Fei-qin
- Jin, Lei
- Wang, Yan-ling
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